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Generating valid test data through data cloning
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DOI：10.1016/j.future.2023.02.020.png)
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Abstract
En 中文
One of the most difficult, time-consuming and error-prone tasks during software testing is that of manually generating the data required to properly run the test. This is even harder when we need to generate data of a certain size and such that it satisfies a set of conditions, or business rules, specified over an ontology. To solve this problem, some proposals exist to automatically generate database sample data. However, they are only able to generate data satisfying primary or foreign key constraints but not more complex business rules in the ontology.We propose here a more general solution for generating test data which is able to deal with expressive business rules. Our approach, which is entirely based on the chase algorithm, first generates a small sample of valid test data (by means of an automated reasoner), then clones this sample data, and finally, relates the cloned data with the original data. All the steps are performed iteratively until a valid database of a certain size is obtained. We theoretically prove the correctness of our approach, and experimentally show its practical applicability.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Database testing
Test data
Data cloning
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